code: def load_data(self, idx):
      text, wav_file, speaker_name = self.items[idx]
      wav = np.asarray(self.load_wav(wav_file), dtype=np.float32)
      mel = self.ap.melspectrogram(wav).astype("float32")
      # sample seq_len
  
      assert text.size > 0, self.items[idx][1]
      assert wav.size > 0, self.items[idx][1]
  
      sample = {
          "mel": mel,
          "item_idx": self.items[idx][1],
          "speaker_name": speaker_name,
      }
      return sample
  
file_path: TTS/TTS/speaker_encoder/dataset.py
imports: import numpy
  import numpy
  import queue
  import torch
  import random
  from torch.utils.data import Dataset
  from tqdm import tqdm
label_desc: Use image node_id 3 for calling the MyDataset obj's underlying member method code with example usage: obj.load_data(idx) and returns: sample